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1 | 1 | """
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2 | 2 | ```julia
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3 |
| -Halley(; chunk_size = Val{0}(), autodiff = Val{true}(), |
| 3 | +SimpleHalley(; chunk_size = Val{0}(), autodiff = Val{true}(), |
4 | 4 | diff_type = Val{:forward})
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5 | 5 | ```
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6 | 6 |
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@@ -28,16 +28,16 @@ and static array problems.
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28 | 28 | `Val{:forward}` for forward finite differences. For more details on the choices, see the
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29 | 29 | [FiniteDiff.jl](https://github.com/JuliaDiff/FiniteDiff.jl) documentation.
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30 | 30 | """
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31 |
| -struct Halley{CS, AD, FDT} <: AbstractNewtonAlgorithm{CS, AD, FDT} |
32 |
| - function Halley(; chunk_size = Val{0}(), autodiff = Val{true}(), |
| 31 | +struct SimpleHalley{CS, AD, FDT} <: AbstractNewtonAlgorithm{CS, AD, FDT} |
| 32 | + function SimpleHalley(; chunk_size = Val{0}(), autodiff = Val{true}(), |
33 | 33 | diff_type = Val{:forward})
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34 | 34 | new{SciMLBase._unwrap_val(chunk_size), SciMLBase._unwrap_val(autodiff),
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35 | 35 | SciMLBase._unwrap_val(diff_type)}()
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36 | 36 | end
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37 | 37 | end
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38 | 38 |
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39 | 39 | function SciMLBase.__solve(prob::NonlinearProblem,
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40 |
| - alg::Halley, args...; abstol = nothing, |
| 40 | + alg::SimpleHalley, args...; abstol = nothing, |
41 | 41 | reltol = nothing,
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42 | 42 | maxiters = 1000, kwargs...)
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43 | 43 | f = Base.Fix2(prob.f, prob.p)
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